Data sensing and compaction condition modeling for asphalt pavements

Abstract

Asphalt pavement compaction is a process of rearranging asphalt particles to reduce voids and increase density. Current empirical methods can sometimes cause compaction problems, particularly when new materials are implemented. This paper develops an innovative monitoring system to determine the compaction condition of asphalt pavement based on particle kinematics. Eleven asphalt mixtures were compacted in the laboratory, and two field compaction projects were carried out. A particle-size wireless sensor, SmartRock, was used to collect the particle kinematic behaviors during compaction. A compaction classification model and a density prediction model were established to predict the compaction condition. Similar particle rotation characteristics were identified under gyratory compaction and roller compaction, allowing the predictive models developed in the laboratory to estimate the field compaction. The predictions are in agreement with the measurement densities, which verifies the applicability of using the particle kinematics and intelligent model to predict the compaction of asphalt pavement.